Grainger Library maintains four public computer terminals on the 1st floor. In addition, the library offers a cluster of computers on the east side of the 1st floor that require an Active Directory Password for access.

NOTE: The Engineering Workstation Labs (EWS) located on the center and east side of the fourth floor can only be used by College of Engineering students.

The Grainger Engineering Library offers some technology items available for loan with an i-Card. These loanable technology items are building use only and most have a two hour loan period. Some of the loanable technology items on reserve include a variety of Apple device charger cables, USB power adapters, HDMI cables, and micro-USB charger cables.

University of Illinois at Urbana-Champaign students may print from the 1st floor computer cluster or from their laptops by paying for their print jobs through their Illini Cash account. Grainger has 6 printers on the first floor: 4 B&W and 2 Color.

Flatbed scanners and a book scanner are available on the first floor. Patrons who are not using the computers to scan materials may be asked to move.

If a photocopy is desired, the best option would be to use one of the aforementioned scanners to scan a copy of the document and print it.

The Engineering Workstations Computer Labs are located on the the 4th floor center and east side of Grainger. EWS are only available to College of Engineering students. Hours of operation are typically the same as the Grainger Engineering Library. For more information, visit the EWS website.

The Center for Academic Resources in Engineering (CARE) provides a study area and tutoring services on the 4th floor of the Grainger Engineering Library. Visit the CARE website for their schedule and more information.

Circulation and Materials

In order to check out materials from the Grainger Engineering Library, all faculty, staff, and students must present a valid i-Card to the circulation staff. All others must present a University of Illinois at Urbana-Champaign courtesy card, a University Laboratory High School ID Card, or an I-Share Member Library ID card.

Loan Periods, Renewals, & Returns

Materials may be renewed online using your library account, in person at a circulation desk, or by calling the Library Telephone Center at (217) 333-8400. Visit the “Request or Renew Items” web page for instructions and additional information.

Please note that I-Share materials can only be renewed online.

Materials may be returned at the Grainger Circulation Desk, the North Circulation Desk, or at the outside Book Drop located on the South East corner. Inter-Library Loan materials must be returned to the Circulation Desk at the Main Library.

Periodicals located at the Grainger Engineering Library are non-circulating and most Standards may be checked out for 2 weeks.

Lost items and billing issues should be directed to Sheila McGowan during regular business hours Monday – Friday. Please include the title and call number of the item along with your name and University Library barcode number on all correspondence.

Reserve materials are located behind the Grainger circulation desk on the first floor. All reserve materials are building use only and usually have a checkout period of two hours. You may renew reserve materials once if no one else has requested it.

There are NO overnight checkout periods for Reserve materials, even on weekends.

Starting Fall 2012, the fine for late return of Reserve materials is $5 per hour.

Requests for materials to be placed on reserve should be submitted 6 weeks before the beginning of each semester. Place reserves using the Request Reserves Form to request materials be put on reserve. Please include department, course number and title. Please prepare class notes, readings, and homework solutions, etc. by inserting them in three-ring binders and bringing subsequent additions prepared to be inserted in the binder.

Data Management

Many federal agencies and other funding agencies have requirements related to the management and/or sharing of digital research data – whether as a section within a proposal or as a separate data management plan. The funder requirements will affect your decisions in all areas outlined in this resource.

Remember that developing and implementing a data management plan is important whether or not your funder requires it!

A current list of funders that require data management plans is available at: https://dmptool.org/public_templates. You should pay careful attention to the funder requirements, particularly if there are more explicit requirements within a specific call for proposals or a directorate (as in the National Science Foundation (NSF)).

We recommend using the DMPTool to develop your data management plan. This online tool will walk you through the process of creating a data management plan by guiding you through a series of questions.

The University Library also maintains a handful of templates for specific funding agencies including:

Data documentation should start at the beginning of a project and continue throughout. This will make data documentation easier and make it less likely that you will forget details later.

What’s important to document?

Context of data collection

Data collection methodology

Structure and organization of data files

Data validation and quality assurance

The manipulation of raw data through analysis

Data confidentiality, access, and use conditions

Data documentation will ensure that your data will be understood and interpreted by any user. It will explain how your data was created, the context of the data, the structure of the data and its contents, and any manipulations that have been applied to the data.

Data Level Documentation

Variable names and descriptions

Definition of codes and classification schemes

Reasons for missing values

Definitions of specialized terminology and acronyms

Algorithms used to transform data

File format and software used

Metadata

Metadata is a standardized way of documenting the origin, purpose, time, geographic location, creator, access, terms of use, and other elements related to the provenance of the data. Metadata provides the essential tools for discovery, access, and reuse of a dataset. There are a variety of metadata standards with different focuses by discipline, international standards, and many other pertinent aspects of a dataset. Some examples of widely adopted metadata standards include the following:

General/Bibliographic Standards

Dublin Core: A general purpose metadata standard for describing a variety of resources.

MODS (Metadata Object Description Schema): a bibliographic element set that may be used for a variety of purposes, and particularly for library applications

METS (Metadata Encoding and Transmission Standard): is a wrapper for several types of metadata pertaining to a resource.

DDI: The Data Documentation Initiative is an effort to establish an international XML-based standard for the content, presentation, transport, and preservation of documentation (i.e., metadata) for datasets in the social and behavioral sciences. The metadata standard created by DDI is called DDI metadata specification, which is often shortened to DDI.

CDWA: Categories for the Description of Works of Art, serves as a foundational framework for the description of cultural heritage materials.

EAD: Encoded Archival Description, a standard for the encoding of finding aids for use in a networked environment.

VRA Core: Visual Resource Association Core Categories, a data standard for the description of works of visual culture as well as the images that document them.

TEI: Text Encoding Initiative, a standard for the digital encoding of literary and linguistic texts.

When creating metadata, a best practice is to use a controlled vocabulary and the standard terminology for your discipline. Consider keeping metadata records in a spreadsheet, CSV file, or tab-delimited file. Additional information needed to interpret the metadata — such as explanations of variables, codes, acronyms or abbreviations, or algorithms used — should be included as accompanying documentation.

Consider the following as an example of a metadata element/value set:

Element

Value

Title

Name of the project of collection of datasets

Creator

Names and institutions of the people who created the data

Date

Key dates associated with the data, such as dates covered by the data or the date of creation

How often have you tried to open an older file only to find that you no longer had access to the software, or that newer software mangled some of the file? What format your data is saved in is one of the most critical elements in how reusable your data will be in the future. Software obsolescence is an important piece of a data management plan and, often, funders require that you describe the formats of your data and the formats that will be shared and preserved.

In addition, defining and documenting how your data will be organized – including file naming and versioning conventions – is an important step in effectively managing your data. While DMPs generally don’t require that you describe this, it is a useful and important process for your own research processes!

File formats

Our ability to preserve digital objects is dependent, among other things, on whether the file format used:

In many cases you may need to actively work with data in a proprietary format, or a format that can only be used with one type of software. Or, the instrument you work with may output to a proprietary format by default. However, when you consider what you will share and/or archive, consider exporting that data to a more open or widely supported format so that it may have the greatest utility in the future. IDEALS maintains a list of file format recommendations based on its preservation support policy.

Organization

Whether you work alone, with a group in a lab, or with a research group, it’s useful to have a defined, documented set of naming and versioning conventions for both the files you are creating as well as the directory structure in which the files live. While establishing such conventions take some set up time, in the long run they can:

Ease finding specific files

Prevent confusion if more than one person is working with files

Minimize chances of overwriting files when it is important to preserve differences

Naming

Establishing a naming convention is a matter of defining and documenting such a convention. Some very basic tips are:

For your directory structure (folders), consider using names that are descriptive of the files in the folder. For projects that go on over a period of time, consider using the year in the file name.

For file names, consider using names that are descriptive of the content of the file.

Avoid characters such as / \ & $ : * in names as these can have specific meanings to an operating system.

Use underscores ( _ ) and not spaces to separate terms.

Keep names short. Some operating systems/software programs have a difficult time parsing long file or folder names.

Versioning

Versioning is generally part of the naming convention. Again, defining and documenting such a convention is helpful.

Use a convention such as v01 appended to the end of the name to indicate versions. Change the version number each time you save a file where you want to distinguish between the changes. For final versions of a file, append FINAL at the end of the name.

If producing software, use a system such as Subversion that tracks changes.

Research Data Sharing and Licensing

Many funding agencies and organizations, and some professional journals, now require that data be shared as a condition of grants, awards, or publication. Beyond fulfilling a requirement, benefits of sharing data include promoting your research, rapid dissemination of results, and furthering related research and discovery.

The University Library provides data services for researchers at any stage of the research process, including grant writing, preparing Data Management Plans (DMP), and finding and managing data during and after the project. Contact the Library at 217-244-1331 or email researchdata@library.illinois.edu.

What is considered data?

Data is essentially factual information and cannot be copyrighted. However, data that is collected, collated or manipulated using significant investment of time or resources may represent an original expression of the data and may be considered copyrightable intellectual property.

In general, the University owns all copyrighted works created as part of a grant or contract and works created as an employment duty or responsibility. For more information about intellectual property and copyright, consult the Government Information Services Intellectual Property Rights information.

Sharing Data

Sharing data can be as simple as emailing it to colleagues or publishing it on a project website. More and more researchers are submitting data to institutional repositories or data centers for archiving, curation, and access. Investigate options carefully as some repositories have their own licensing policies and guidelines while others allow you to choose.

Basic Steps for Sharing Data

Determine what data, database, or datasets are to be shared

Select and apply license

What intellectual property rights are associated with the data?

Select an appropriate license that works with the Intellectual Property rights.

Make the data available

Provide data in a user-friendly format.

Make it find-able

Provide thorough and clear metadata and documentation for your datasets.

Considerations for Original Data

Be sure you understand any and all permissions related to your research. Before you share or license research data you need to know if your work is copyrightable, who holds the copyright (you or your institution), and whether or not your institution maintains licensing privileges.

Are there specific terms of the grant that dictate how data should be shared/licensed/disseminated?

Will data include private, personal, or medical information? Consider stipulations of IRB approval.

Will you want to request or require acknowledgement, attribution, or reporting of data usage?

Will you allow data to be re-used and, if so, will it be restricted to non-commercial use only?

If the data is the result of a collaborative research project, you need to have permission from all parties before granting license for use.

Beware of Attribution Stacking: repeated iterations of third party data all requiring attribution.

If you require attribution, consider providing citation information and formatting.

Considerations for Third Party Data or Materials
If your data was derived using third party data, stipulations of the third party data use must be reflected in the license selection for your derivative data.

What are expectations or parameters under which the third party data may be used?

What are the limitations for use of the data?

What permissions are needed to disseminate research findings resulting from use of the data?

Are there costs associated with use of third party data, and how will they be covered?

Material Transfer Agreement

Materials or technology that are coming into the University for research purposes require a Material Transfer Agreement in order to protect intellectual property rights and acceptable use. (Office of the Vice Chancellor for Research)

Licensing your Research Data

About Licenses

There is a spectrum of permissions that can be assigned to licensing data for use, re-use, or distribution. The least restrictive license states that anyone can use, reuse, share and re-distribute the data for any purpose and without attribution. In essence, you waive your claim to the copyright. Restrictions that can be added to a license include:

Attribution – If you allow use or re-use of the data you will need to decide if the license will require the inclusion of attribution or acknowledgement in resulting output.

Reporting/Notification — You may request or require users of the data to report their use back to you.

Derivative Works – Will you allow re-use of your data in the creation of derivative works? With or without attribution? You can stipulate that any derivative work(s) must be licensed under the same parameters as your data; this is called “ShareAlike.”

Commercial/Non-Commercial Use – Will you allow re-use of your data for commercial use or for non-commercial use exclusively?

Licensing Groups/Organizations

IDEALS: University of Illinois at Urbana-Champaign’s Institutional Repository

By default, items in IDEALS have no access restrictions; they are openly and freely available via the World Wide Web. However, there may be some situations when depositors need to restrict access to items in IDEALS. For example, a publisher may allow deposit of published articles into an institutional repository but require an embargo of six months before the article may be made publicly accessible.

IDEALS allows access restrictions to be imposed at the collection or item level. The individual depositor or the IDEALS community (the group responsible for a set of collections in IDEALS) is responsible for the decision to impose access restrictions.

Open Data Commons – Provides legal licensing language for making available and using open data:

PDDL – Public Domain Dedication and License – places data in the public domain, free for anyone to use and share

ODC-By – Attribution License – data or data sets are free for anyone to use but they must provide attribution to the source

ODC – Odbl – Open Database License – data or data sets are free to use but any resulting use of data must provide attribution to the original source and any resulting new output must be made available under the same license terms

Restriction

What it means

IDEALS

None – Open Access

In the public domain; free for anyone to use or share without conditions

Default License

Attribution

Any use or re-use must include attribution to original source

NA

Share Alike

Any derivative works must be available under the same license as original

NA

Access

Access to data or sets of data is restricted to specific groups or for a specific time period

Level 1: Restricted to University of Illinois community members with a NetID and password only;

Level 2: Restricted to a specific group defined and maintained within IDEALS

Storage, backups, and security are fundamental aspects of a data management plan. Ensuring them may involve working with your local IT unit, CITES, and, where appropriate, with NCSA to choose appropriate options for your data.
There is an important distinction to be made between short-term and long-term storage. On this page we are referring to short-term storage as where you collect and manage your data while you are processing and analyzing it, rather than where you might archive the data for longer term preservation, curation, and sharing purposes.
Backups refer to the creation of additional copies of your data that can be used to restore data if the original is damaged or deleted. The general rule of thumb is that you should have three copies of your data:

Original

Original + local

Original + remote

Security involves maintaining the integrity of the data on the storage system and backups, as well as ensuring that sensitive or confidential data is managed in a way that is compliant with university, state, and federal regulations, in addition to the requirements of the funder.
Issues to consider in this area:

What is the expected growth rate of your data? Is data collected in an automated fashion (e.g. sensors) or is it gathered by staff?

Are there particular security issues you need to consider with the data? Do you need to comply with regulations around sensitive or confidential data?

Do you need to manage data so that only specific users are authorized to access it? Do you need to grant collaborators from off campus access to the data? Do you need to have an audit trail that tracks access and/or changes to the data?

Is the data backed up reliably and adequately? Are the backups securely managed? Are there policies or regulatory requirements to encrypt sensitive data that is backed up? In many cases, particularly when working with medium to large size datasets, you should contact your local or college level IT unit for assistance with storage, backups, and security. These units can help you identify the cost of storage and the needed infrastructure for security and backups. If there are security assurances that you will need to provide to the funder, you will want to contact the CITES Security Group for assistance. As always, the earlier you talk with your IT unit in a grant planning process, the better!